The present disclosure relates to the well-known acoustic feedback problem in audio systems comprising a forward path for amplifying an input sound from the environment picked up by an acoustic input transducer and an output transducer for presenting an amplified version of the input signal as an output sound to the environment, e.g. to one or more users.
Acoustic feedback occurs because the output transducer (e.g. loudspeaker) signal from an audio system providing amplification of a signal picked up by an input transducer (e.g a microphone) is partly returned to the microphone via an acoustic coupling through the air or other media. The part of the loudspeaker signal returned to the microphone is then re-amplified by the system before it is re-presented at the loudspeaker, and again returned to the microphone. As this cycle continues, the effect of acoustic feedback becomes audible as artifacts or even worse, howling, when the system becomes unstable. The problem appears typically when the microphone and the loudspeaker are placed closely together, as e.g. in hearing aids or other audio systems. Some other classic situations with feedback problem are telephony, public address systems, headsets, audio conference systems, etc. Feedback cancellation (or reduction) is typically provided by subtracting an estimate of the feedback signal from the input signal to provide a feedback corrected input signal. Adaptive feedback estimation has the ability to track feedback path changes over time. It is based on a linear time invariant filter to estimate the feedback path but its filter weights are updated over time. The filter update may be calculated using stochastic gradient algorithms, e.g. including some form of the Least Mean Square (LMS) or the Normalized LMS (NLMS) algorithms. They both have the property to minimize an error signal (e.g. the feedback corrected input signal) in the mean square sense, with the NLMS additionally normalizing the filter update with respect to the squared Euclidean norm of some reference signal (e.g. the output signal). The success of the above mentioned method is dependent on its ability to provide an up to date feedback path estimate in a dynamic acoustic environment (including to be able to distinguish between tonal components originating from the environment and tonal components due to feedback). It may be a challenge to control the adaptation rate of an adaptive algorithm to follow the dynamics of the acoustic environment.
EP2148527A1 deals with a hearing aid system comprising left and right hearing aid devices for completely eliminating the acoustic feedback by using inter-aural signal transmission (cross-over of respective microphone signals to the opposite device) and application of binary (complementary) gain patterns in the respective hearing aid devices.
US2015011266A1 deals with a speakerphone for use in a teleconference setup wherein a complementary filtering scheme is applied in the microphone and loudspeaker paths, respectively.